Lead Data Scientist
פורסם 28 במאי · 96 מועמדים
התפקיד במילים פשוטות
בתפקיד זה, תהיה אחראי על מחזור החיים המלא של למידת מכונה, כולל ניתוח נתונים, פיתוח מודלים, פריסה לייצור, ניטור ואופטימיזציה. כמו כן, תוביל את התכנון והפיתוח של מערכות AI גנרטיביות וסוכנותיות לשימוש בייצור, ותגדיר ותאכוף תקני איכות עבורן.
- Own the full machine learning lifecycle: data analysis, model development, ideation, proof of concept, production deployment, monitoring, and optimization
- Lead the design, development, evaluation, and optimization of agentic and generative AI systems for production use
- Define and enforce quality standards for agentic AI, ensuring reliability, consistency, business relevance, and compliance
- Develop robust methods to evaluate, monitor, and set guardrails for non-deterministic AI systems
- Optimize AI solutions across accuracy, latency, and cost
חולץ מתיאור המשרה · מתעדכן אוטומטית
למי זה מתאים
התפקיד מתאים למועמדים בעלי תואר שני או דוקטורט במתמטיקה, סטטיסטיקה, מדעי המחשב או תחום כמותי קשור, עם ניסיון עשיר בתכנות בפייתון, למידת מכונה ולמידה עמוקה. נדרש גם ניסיון במערכות המלצה והתאמה אישית, וכן רקע חזק בסטטיסטיקה תיאורטית.
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןOur Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title And Summary
Lead Data Scientist
Job Description
Own the full machine learning lifecycle: data analysis, model development, ideation, proof of concept, production deployment, monitoring, and optimization
Lead the design, development, evaluation, and optimization of agentic and generative AI systems for production use
Define and enforce quality standards for agentic AI, ensuring reliability, consistency, business relevance, and compliance
Develop robust methods to evaluate, monitor, and set guardrails for non-deterministic AI systems
Optimize AI solutions across accuracy, latency, and cost
Build and maintain self-optimized and continuously learning algorithms
Drive advanced personalization initiatives, including personalized ranking, and contextual recommendation strategies
Apply cutting-edge AI techniques to solve complex business problems
Lead rigorous experimentation and statistical analysis to guide decision-making and validate impact
Conduct ongoing research by analyzing industry trends, academic publications, and competitor approaches to drive innovation
Requirements
Master’s/PhD in Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, or equivalent practical experience
Strong programming skills in Python, Github, Vibe Coding
Solid background in theoretical statistics
Hands-on experience in machine learning and deep learning
Intensive experience in structured and unstructured data
Proven experience with recommendation systems and personalization
Experience in data analysis, experimentation, and visualization
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Abide by Mastercard’s security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
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שאלות על המשרה
- המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
- Own the full machine learning lifecycle: data analysis, model development, ideation, proof of concept, production deployment, monitoring, and optimization, Lead the design, development, evaluation, and optimization of agentic and generative AI systems for production use, Define and enforce quality standards for agentic AI, ensuring reliability, consistency, business relevance, and compliance, Develop robust methods to evaluate, monitor, and set guardrails for non-deterministic AI systems, Optimize AI solutions across accuracy, latency, and cost